Könyv Sparse Grid Methods for Higher Dimensional Approximation Christian Feuersänger

Sparse Grid Methods for Higher Dimensional Approximation

Theory and Experiments on Benefits and Limitations of Sparse Grid Approximation Methods and Generalizations to Low Effective Dimensionality

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Kiadói készleten rendelésre
Küldés 17-27 napon belül
31 030 Ft
Approximation of functions depending on more than three variables is relevant for the simulation of...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
184
EAN
9783838121406
ISBN
3838121406
Enbook ID
06936935
Súly
288
Méretek
152 x 229 x 18

Teljes leírás

Approximation of functions depending on more than three variables is relevant for the simulation of dynamic models. Especially stochastic models lead to a wide range of applications like simulation of polymeric liquids, kinetic equations for forces acting on offshore wind parks, or even the pricing of financial products. Sparse Grids have been designed to significantly reduce the cost to approximate high-dimensional functions under certain smoothness conditions. This book presents tools to design and work with Sparse Grids, including construction properties, algorithms, data structures and error estimates. It also discusses inherent limitations and their benefits when it comes to the simulation of stochastic models, namely to the representation of probability density functions. Furthermore, the book reveals new space- and dimension-adaptive Sparse Grids which are suitable for functions that effectively depend on only a few of their input variables.

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